Visualizing and analyzing georeferenced workloads of mobile networks

The comprehension of human mobility patterns can help governments and private sectors to improve the quality of services offered to population. Characterizing and understanding the different workloads generated on mobile networks during different kind of events are a challenge for carriers, who should keep connectivity services always on. The visualization and analysis of such workloads can drive a better planning of the network infrastructure for different kinds of events. This work presents an approach for visualizing and analyzing georeferenced data of mobile networks usage, specially on events which generate unplanned workloads. In order to support our approach we built a system named the Geo-Data Visualizer. We show the capability of our system to visualize the mobile network usage as well as the dynamics and movement of network users during a period of time using three real datasets.